def deploy_states_api(disable_validation, input_dir, output, summary_output):
"""The entry function for invocation"""
# check that the dirs exist before starting
for directory in [input_dir, output, summary_output]:
if not os.path.isdir(directory):
raise NotADirectoryError(directory)
for intervention in list(Intervention):
logger.info(f"Running intervention {intervention.name}")
states_result = api_pipeline.run_projections(
input_dir,
AggregationLevel.STATE,
intervention,
run_validation=not disable_validation,
)
state_summaries, state_timeseries = api_pipeline.generate_api(states_result, input_dir)
api_pipeline.deploy_results([*state_summaries, *state_timeseries], output)
states_summary = api_pipeline.build_states_summary(
state_summaries, intervention
)
states_timeseries = api_pipeline.build_states_timeseries(
state_timeseries, intervention
)
summarized_timeseries = api_pipeline.build_prediction_header_timeseries_data(states_timeseries)
api_pipeline.deploy_prediction_timeseries_csvs(summarized_timeseries, summary_output)
api_pipeline.deploy_results([states_summary], summary_output, write_csv=True)
api_pipeline.deploy_results([states_timeseries], summary_output)
def deploy_counties_api(disable_validation, input_dir, output, summary_output):
"""The entry function for invocation"""
# check that the dirs exist before starting
for directory in [input_dir, output, summary_output]:
if not os.path.isdir(directory):
raise NotADirectoryError(directory)
for intervention in list(Intervention):
county_result = api_pipeline.run_projections(
input_dir,
AggregationLevel.COUNTY,
intervention,
run_validation=not disable_validation,
)
county_summaries, county_timeseries = api_pipeline.generate_api(
county_result, input_dir)
api_pipeline.deploy_results([*county_summaries, *county_timeseries],
output)
counties_summary = api_pipeline.build_counties_summary(
county_summaries, intervention)
counties_timeseries = api_pipeline.build_counties_timeseries(
county_timeseries, intervention)
summarized_timeseries = api_pipeline.build_prediction_header_timeseries_data(
counties_timeseries)
api_pipeline.deploy_prediction_timeseries_csvs(summarized_timeseries,
summary_output)
api_pipeline.deploy_results([counties_summary],
summary_output,
write_csv=True)
api_pipeline.deploy_results([counties_timeseries], summary_output)
logger.info("finished top counties job")
def deploy_counties_api(disable_validation, input_dir, output, summary_output):
"""The entry function for invocation"""
for intervention in list(Intervention):
# TODO(issues/#258): remove check once counties support inferrence
if intervention in Intervention.county_supported_interventions():
county_result = api_pipeline.run_projections(
input_dir,
AggregationLevel.COUNTY,
intervention,
run_validation=not disable_validation,
)
county_summaries, county_timeseries = api_pipeline.generate_api(
county_result, input_dir
)
api_pipeline.deploy_results([*county_summaries, *county_timeseries], output)
counties_summary = api_pipeline.build_counties_summary(county_summaries, intervention)
counties_timeseries = api_pipeline.build_counties_timeseries(county_timeseries, intervention)
summarized_timeseries = api_pipeline.build_prediction_header_timeseries_data(counties_timeseries)
api_pipeline.deploy_prediction_timeseries_csvs(summarized_timeseries, summary_output)
api_pipeline.deploy_results([counties_summary], summary_output, write_csv=True)
api_pipeline.deploy_results([counties_timeseries], summary_output)
logger.info("finished top counties job")
def deploy_states_api(disable_validation, input_dir, output):
"""The entry function for invocation"""
for intervention in list(Intervention):
states_result = api_pipeline.run_projections(
input_dir,
AggregationLevel.STATE,
intervention,
run_validation=not disable_validation,
)
states_results_api = api_pipeline.generate_api(states_result)
api_pipeline.deploy_results(states_results_api, output)
logger.info("finished top counties job")
def deploy_states_api(disable_validation, input_dir, output, summary_output):
"""The entry function for invocation"""
for intervention in list(Intervention):
logger.info(f"Running intervention {intervention.name}")
states_result = api_pipeline.run_projections(
input_dir,
AggregationLevel.STATE,
intervention,
run_validation=not disable_validation,
)
state_summaries, state_timeseries = api_pipeline.generate_api(states_result, input_dir)
api_pipeline.deploy_results([*state_summaries, *state_timeseries], output)
states_summary = api_pipeline.build_states_summary(
state_summaries, intervention
)
states_timeseries = api_pipeline.build_states_timeseries(
state_timeseries, intervention
)
summarized_timeseries = api_pipeline.build_prediction_header_timeseries_data(states_timeseries)
api_pipeline.deploy_prediction_timeseries_csvs(summarized_timeseries, summary_output)
api_pipeline.deploy_results([states_summary], summary_output, write_csv=True)
api_pipeline.deploy_results([states_timeseries], summary_output)
def deploy_states_api(disable_validation, input_dir, output, summary_output):
"""The entry function for invocation"""
for intervention in list(Intervention):
states_result = api_pipeline.run_projections(
input_dir,
AggregationLevel.STATE,
intervention,
run_validation=not disable_validation,
)
states_results_api = api_pipeline.generate_api(states_result,
input_dir)
api_pipeline.deploy_results(states_results_api, output)
states_summary = api_pipeline.build_states_summary(
states_results_api, intervention)
states_timeseries = api_pipeline.build_states_timeseries(
states_results_api, intervention)
api_pipeline.deploy_results([states_summary],
summary_output,
write_csv=True)
api_pipeline.deploy_results([states_timeseries], summary_output)
logger.info("finished states job")